class_docstr: The Missing Values Dispersion visualizer shows the locations of missing (nan)
  values in the feature dataset by the order of the index.
  
  When y targets are supplied to fit, the output dispersion plot is color
  coded according to the target y that the element refers to.
  
  Parameters
  ----------
  alpha : float, default: 0.5
      A value for bending elments with the background.
  
  marker : matplotlib marker, default: |
      The marker used for each element coordinate in the plot
  
  classes : list, default: None
      A list of class names for the legend.
      If classes is None and a y value is passed to fit then the classes
      are selected from the target vector.
  
  kwargs : dict
      Keyword arguments that are passed to the base class and may influence
      the visualization as defined in other Visualizers.
  
  Attributes
  ----------
  features_ : np.array
      The feature labels ranked according to their importance
  
  classes_ : np.array
      The class labels for each of the target values
  
  Examples
  --------
  
  >>> from yellowbrick.contrib.missing import MissingValuesDispersion
  >>> visualizer = MissingValuesDispersion()
  >>> visualizer.fit(X, y=y)
  >>> visualizer.show()
docstr: Sets the title and x-axis label and adds a legend. Also ensures that
  the y tick labels are set to the feature names.
  
  Parameters
  ----------
  kwargs: generic keyword arguments.
  
  Notes
  -----
  Generally this method is called from show and not directly by the user.
docstr_tok: ["Sets","the","title","and","x-axis","label","and","adds","a","legend",".","Also","ensures","that","the","y","tick","labels","are","set","to","the","feature","names",".","Parameters","--","--","--","--","--","kwargs",":","generic","keyword","arguments",".","Notes","--","--","-","Generally","this","method","is","called","from","show","and","not","directly","by","the","user","."]
code: def finalize(self, **kwargs):
      """
      Sets the title and x-axis label and adds a legend. Also ensures that
      the y tick labels are set to the feature names.
  
      Parameters
      ----------
      kwargs: generic keyword arguments.
  
      Notes
      -----
      Generally this method is called from show and not directly by the user.
      """
      # Set the title
      self.set_title("Dispersion of Missing Values by Feature")
      # the x locations for the groups
      tick_locations = np.arange(len(self.features_))
  
      self.ax.set_xlabel("Position by index")
      self.ax.set_yticks(tick_locations)
      self.ax.set_yticklabels(self.get_feature_names())
      self.ax.legend(
          loc="upper left", prop={"size": 5}, bbox_to_anchor=(1, 1)
      )
  
file_path: yellowbrick/yellowbrick/contrib/missing/dispersion.py
imports: import numpy
  from yellowbrick.style.palettes import color_palette
  from .base import MissingDataVisualizer
label_desc: Use image node_id 5 for calling the MissingValuesDispersion obj's underlying member method code with example usage: obj.finalize() without return types